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The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility.

The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis.

The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility.

This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.

After the end of World War II, Switzerland became a key hub for international commodity traders, even though most of the commodities they were dealing in were sourced from outside of Switzerland and were not meant for Swiss producers, refiners or consumers. The main aim of this chapter is to analyze why Switzerland became the centre for international commodity trading in the Western world. The chapter will especially focus on the period from the 1950s to the end of the 1980s. Given that commodity trading companies throughout history have been notoriously closed to external scrutiny, the chapter by need is mainly based on publicly available material. The chapter utilizes the concept of collective entrepreneurship as an analytical framework to situate the development.

The Indian commodity market requires large investments and enhanced trading activity both in the national as well as the regional commodity markets. The participation of non‐professional people trading commodity markets makes the market a risky venture. Non‐professional participants simply add to the volatility factor of the market. There is a dire need for professional experts who are able to provide advice on commodity trading and build commodity inclusive portfolios. Such professional awareness, expertise, and guidance in commodity trading can come from professional commodity traders called commodity trading advisors (CTAs). The purpose of this paper is to offer arguments and insights as to why the Indian commodity market needs the participation of the CTAs. The money brought in by CTA advised clients will add to the depth, liquidity, and trade which in turn will make commodity prices more efficient. As a regulatory measure, the Indian market too can adopt guidelines structured for CTAs by Commodity Future Trading Commission and National Futures Association. The CTAs can bring the Indian commodity market at par with developed commodity markets like Chicago Board of Trade.

The paper reviews and discusses the various issues related to CTAs applicability in India. The goal of the paper is to outline the need for allowing CTAs activity in Indian commodity market and discuses the key operational and policy considerations in developing the commodity market for CTAs in India.

The recent expansion of Indian commodity market has not been very structured. The market has expanded with the expansion in demand for commodities both in spot and derivative market. There have been constraints through policy restrictions and at the same time there has been an effort for liberalization of the commodity market to bring them at par with international commodity market. Of late, the Indian equity market has been very volatile. Participation of CTAs will provide much required downside protection to traditional portfolios and they will also provide the expertise in commodity derivative trading to participants and help build the commodity inclusive portfolios with better return and lesser risk.

This is the first paper that initiates thoughts on allowing CTAs to participate in the Indian commodity market. The paper builds on the concept that CTAs would add the desired price discovery, volume, and depth to the Indian commodity market. The Indian commodity market, despite being quite old, has recently broken free from the restrictive policies and has ushered into an era of initiates supporting commodity derivative market development. To the best of the authors' knowledge, there exists no literature on CTAs participation in India.

To alert participants in the commodities markets to an important development in the exercise of enforcement authority by the Commodity Futures Trading Commission.

Explains a recent proceeding which resulted in the CFTC’s first-ever application of a newly-promulgated regulatory Rule to punish “insider trading” involving the commodities markets.

The CFTC has shown that it intends to apply its new Rule aggressively to address insider trading in the commodities markets.

As a result of the CFTC’s new enforcement approach to regulating insider trading in the areas under its jurisdiction, all participants in the commodities markets must be attuned to the prohibition on insider trading, familiar with actions that might be deemed unlawful insider trading, and act accordingly to avoid improper trading activities.

Practical guidance for participants in the commodities markets from an experienced attorney with expertise in government enforcement matters.

The purpose of this paper is to compare the profitability of different pairs selection and spread trading methods using the complete data set of commodity futures from Dalian Commodity Exchange, Shanghai Futures Exchange and Zhengzhou Commodity Exchange.

Paris trading methods that are proposed in the literature are compared in terms of the risk-adjusted returns visa in-sample and out-of-sample backtesting and bootstrapping for robustness.

The empirical results show that pairs trading in the Chinese commodity futures market offers high returns, whereas, the profitability of these strategies primarily depends on the identification of suitable pairs. The observed high returns are a compensation for the spread divergence risk during the potentially longer holding periods, which implies that the maximum drawdown is more crucial compared to other risk-adjusted return measures such as the Sharpe ratio.

Complementary to the existing literature, for the Chinese commodity futures market, it is shown that if shorter maximum holding periods are introduced for the spread positions, then the pairs trading profits decreases. Therefore, the returns do not necessarily imply market inefficiency when the higher maximum drawdown associated with the holding period of the spread position is taken into account.

This study aims to examine the illicit capital movement through trade misinvoicing in Burundi, at disaggregated levels by major trading partners and by major export and import commodities.

Trade misinvoicing is estimated by comparing the trade values declared by Burundi with those declared by trading partners in a bilateral international transaction, after adjusting for the cost of freight and insurance. Disaggregated trade misinvoicing by major trading partners is computed using the Direction of Trade Statistics database of the International Monetary Fund over the period 1970–2019. Disaggregated trade misinvoicing by major trading commodities is computed using the UN-COMTRADE database over the period 1993–2019.

Exports of Burundi to most of its major trading partners are found to be underinvoiced. The top destinations for export underinvoicing are United Arab Emirates, Belgium and Germany. However, exports to UK and Switzerland are found to be overinvoiced. The major export commodities considered, coffee and gold, are found to be affected by trade misinvoicing to a great extent. On the import side, the estimation results indicate that imports of Burundi from its major trading partners are in general overinvoiced. High import overinvoicing is observed in the trade with Saudi Arabia, China and Japan. At commodity level, for the top 6 commodities considered, imports were to a great extent found to be overinvoiced. Cases of illicit capital outflows and inflows through trade misinvoicing are highlighted.

Some policy implications are drawn from this study. First, in collaboration with its development partners, the Government of Burundi should put in place measures to reduce the trade misinvoicing phenomenon, which undermines poverty reduction efforts. The study has shown which trade partners are involved and which commodities are mostly affected. Policy efforts could then be focused in that regard. Investigations at the company and transaction levels can be made to identify the mechanisms of trade misinvoicing. Second, more effort is needed in ensuring systematic and transparent reporting of international trade transactions. To fight trade misinvoicing, transparency in international trade is key, through coordinated enforcement of reporting rules.

Previous studies analyzed the problem of trade misinvoicing at an aggregated level. However, this leaves out essential information on trading partners involved in the phenomenon as well as trading commodities affected. This study investigates trade misinvoicing at disaggregated levels, at product level and by trading partner.

The purpose of this paper is to apply an analysis of complex networks to empirically research international agricultural commodity trade and countries’ trading relations. The structure of global agricultural commodity trade is quantitatively described and analysed.

Based on statistical physics and graph theory, the research paradigm of a complex network, which has sprung up in the last decade, provides us with new global perspective to discuss the topic of international trade, especially agricultural commodity trade. In this paper, the authors engage in the issue of countries’ positions in international agricultural commodity trade using the latest complex network theories. The authors at first time introduce the improved bootstrap percolation to simulate cascading influences following the breaking down of bilateral agricultural commodity trade relations.

On a mid-level structure, countries are classified into three communities that reflect the structure of the “core/periphery” using the weighted extremal optimisation algorithm and the coarse graining process. On a micro-level, countries’ rankings are provided with the aid of network’s node centralities, which presents world agricultural commodity trade as a closed, imbalanced, diversified and multi-polar development.

The authors at first time introduce the improved bootstrap percolation to simulate cascading influences following the breaking down of bilateral agricultural commodity trade relations.

This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large commodity portfolio and in obtaining efficient and coherent portfolios under different market circumstances.

The implemented market risk modeling algorithm and investment portfolio analytics using reinforcement machine learning techniques can simultaneously handle risk-return characteristics of commodity investments under regular and crisis market settings besides considering the particular effects of the time-varying liquidity constraints of the multiple-asset commodity portfolios.

In particular, the paper implements a robust machine learning method to commodity optimal portfolio selection and within a liquidity-adjusted value-at-risk (LVaR) framework. In addition, the paper explains how the adapted LVaR modeling algorithms can be used by a commodity trading unit in a dynamic asset allocation framework for estimating risk exposure, assessing risk reduction alternates and creating efficient and coherent market portfolios.

The optimization parameters subject to meaningful operational and financial constraints, investment portfolio analytics and empirical results can have important practical uses and applications for commodity portfolio managers particularly in the wake of the 2007–2009 global financial crisis. In addition, the recommended reinforcement machine learning optimization algorithms can aid in solving some real-world dilemmas under stressed and adverse market conditions (e.g. illiquidity, switching in correlations factors signs, nonlinear and non-normal distribution of assets’ returns) and can have key applications in machine learning, expert systems, smart financial functions, internet of things (IoT) and financial technology (FinTech) in big data ecosystems.

This study aims to validate the “expectancy theory” of asset pricing and explores the price discovery process in metals futures markets.

This paper adopts the Johansen cointegration and vector error correction model approach to investigate the potentials of Pairs trading in the metals market during the period 2008–2019.

The results find the price movements in metal markets are not random walk and the current “futures” prices are the reasonable estimate of the “spot” metal prices in future. This study does not notice any significant differences in the price efficiency across metals markets, which signal the effects of limited idiosyncratic forces in price transmission.

The research suggests the covert use of metal futures to make gains from arbitrage trading.

The study emphasizes the potential of “pair trading” in commodity market context that is seldom discussed in academic papers.

Guar Seed crop is ruling the Indian International business mainly due to its application as a drilling fluid in shale energy industry concentrated in the USA. One of the allegations against futures market is its possible role in increasing the volatility of underlying physical market prices. Suspension of guar seed futures contract in 2012 at National Commodity Derivatives Exchange of India (NCDEX)-India, has reignited the controversy and raised an alarm bell to peek into obscure world of Indian commodity derivatives market. Against the backdrop of fiasco in guar futures trading, the purpose of this paper is to investigate whether sudden surge in futures trading volume leads to increase in the volatility of spot market prices.

Guar seed spot returns volatility is modeled as a GARCH (1, 1) process. Futures trading volume and open interest are segregated into expected and unexpected components. The data are analyzed from 2004 to 2011 using Augmented GARCH model to study the contemporaneous relationship between spot volatility and unexpected futures trading activity and Granger Causality test for examining the dynamic relationship between them and ascertaining causality.

Augmented GARCH model reports positive relationship between unexpected futures trading volume (UTV) and spot returns volatility, and, Granger Causality flows from UTV to spot volatility. Therefore, when the level of futures trading volume increases unexpectedly, the volatility of spot prices increases pointing toward the destabilizing impact of futures trading. However, hedger’s activity, represented by open interest is not seen to have any causal/destabilizing impact on spot price volatility of guar seed.

The study provides empirical evidence to support the concern of regulators, genuine hedgers and other traders about the presence of excessive speculation and market manipulations perpetrated through futures market that is disturbing the underlying physical market instead of strengthening it by aiding in price discovery and risk mitigation.

There are very few studies which have empirically investigated the temporal relation between volume and volatility in Indian agricultural commodity markets. With guar seed as a special case the present study investigates statistically the impact of futures trading on spot price volatility. In light of the findings of the study, the curb imposed on guar seed futures trading in 2012 was justified.